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Does a positive density perception increase the probability of living in the ideal housing type? Evidence from the Loire-Atlantique Département in France

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  • Rémy Le Boennec
  • Sterenn Lucas

Abstract

What does the ideal housing type look like? A 2015 online survey of individuals living in the Loire-Atlantique Département in France provided 1,134 interviews, which we analyze using a mixed-effect probit model. We look at the probability of living in the ideal housing type related to 28 variables of dwelling and respondent characteristics, density perception, district perception, type of municipality, and proximity to education, healthcare and food facilities. The issue is important because certain housing types yield greater land consumption and longer trips. Local governments support infill developments with higher built-up density levels to conserve land and support walking, cycling, and transit. We find that the probability of living in the ideal housing type has no relationship to density perception. What matters is a positive district perception and proximity to healthcare. Well-designed infill development with higher built-up density levels can succeed, associating a higher probability of living in the ideal housing type with suitable urban forms given the physical constraints of territories, in a sustainable development framework.

Suggested Citation

  • Rémy Le Boennec & Sterenn Lucas, 2020. "Does a positive density perception increase the probability of living in the ideal housing type? Evidence from the Loire-Atlantique Département in France," Working Papers SMART 20-01, INRAE UMR SMART.
  • Handle: RePEc:rae:wpaper:202001
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    More about this item

    Keywords

    housing type; density perception; district perception; built-up density; mixed-effect probit model;
    All these keywords.

    JEL classification:

    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns
    • R28 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Government Policy
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • D62 - Microeconomics - - Welfare Economics - - - Externalities

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